Identification of serum prognostic biomarkers of severe COVID-19 using a quantitative proteomic approach.
Sci Rep
; 11(1): 20638, 2021 10 19.
Article
in English
| MEDLINE | ID: covidwho-1475483
ABSTRACT
The COVID-19 pandemic is an unprecedented threat to humanity that has provoked global health concerns. Since the etiopathogenesis of this illness is not fully characterized, the prognostic factors enabling treatment decisions have not been well documented. Accurately predicting the progression of the disease would aid in appropriate patient categorization and thus help determine the best treatment option. Here, we have introduced a proteomic approach utilizing data-independent acquisition mass spectrometry (DIA-MS) to identify the serum proteins that are closely associated with COVID-19 prognosis. Twenty-seven proteins were differentially expressed between severely ill COVID-19 patients with an adverse or favorable prognosis. Ingenuity Pathway Analysis revealed that 15 of the 27 proteins might be regulated by cytokine signaling relevant to interleukin (IL)-1ß, IL-6, and tumor necrosis factor (TNF), and their differential expression was implicated in the systemic inflammatory response and in cardiovascular disorders. We further evaluated practical predictors of the clinical prognosis of severe COVID-19 patients. Subsequent ELISA assays revealed that CHI3L1 and IGFALS may serve as highly sensitive prognostic markers. Our findings can help formulate a diagnostic approach for accurately identifying COVID-19 patients with severe disease and for providing appropriate treatment based on their predicted prognosis.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Biomarkers
/
Gene Expression Profiling
/
Proteomics
/
COVID-19 Serological Testing
/
COVID-19
Type of study:
Diagnostic study
/
Experimental Studies
/
Prognostic study
Limits:
Humans
Language:
English
Journal:
Sci Rep
Year:
2021
Document Type:
Article
Affiliation country:
S41598-021-98253-9
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